Data Engineer

remopt

Engenheiro de Dados Sênior construindo pipelines e arquiteturas escaláveis para operadora de telecomunicações. Transformando dados de rede móvel e sistemas corporativos em insights estratégicos.

Posted 8/20/2026full-timeSão Paulo • 🇧🇷 BrazilMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in Data Engineering, Data Modeling, and the development of scalable data architectures. Proficient in advanced SQL, Python, and ETL/ELT processes to support data-driven solutions in telecommunications.

Highest-signal resume keywords

Data EngineeringData ModelingAdvanced SQLETL/ELT ProcessesData Quality Practices

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data EngineeringData ModelingETL/ELT ProcessesData Quality PracticesData GovernanceData ArchitectureAdvanced SQLPythonPySparkREST APIs

Tools & Technologies

HadoopAzure Data PlatformKafkaDatabricksAirflowSnowflakeAWSGoogle Cloud Platform

Industry Keywords

Telecom KnowledgeGSMUMTSLTE5GRANCoreTransportOSS ArchitecturesNetwork KPIs

Tech Stack

Tools & technologies

AirflowAWSAzureCloudElasticSearchETLGoogle Cloud PlatformHadoopKafkaMongoDBOraclePySparkPythonSparkSQL

About the role

Key responsibilities & impact

Develop high-volume data ingestion, processing and transformation pipelines
Design and evolve scalable, resilient data architectures
Integrate data from OSS, BSS, corporate platforms and APIs
Ensure data quality, governance, traceability and monitoring
Provide data for Business Intelligence, Analytics, Machine Learning and Artificial Intelligence initiatives
Translate mobile network technical indicators into data models that support strategic decisions
Collaborate with Engineering, Operations, Technology and Business teams to build data-driven solutions
Build and evolve the data platform for a telecommunications operator

Requirements

What you’ll need

Experience in Data Engineering
Experience in Data Modeling
Knowledge of Data Lake and Data Warehouse concepts
Knowledge of ETL/ELT processes
Experience with Data Pipelines
Knowledge of Data Quality practices
Knowledge of Data Governance and Data Architecture
Advanced SQL
Python
PySpark / Spark
REST APIs
Shell scripting
Hadoop
Azure Data Platform
Kafka
Familiarity with Databricks, Airflow, Snowflake, AWS and Google Cloud Platform (desirable)
Familiarity with Oracle, SQL Server, MongoDB and Elasticsearch databases (desirable)
Telecom knowledge (advantage): GSM, UMTS, LTE and 5G (NSA and SA)
Knowledge of RAN, Core, Transport and OSS architectures (advantage)
Knowledge of network KPIs such as Availability, Accessibility, Retention, Throughput, Latency, QoS and QoE (advantage)
Experience with PM Counters, CDRs, Alarms, Drive Tests, OSS logs and regulatory data (advantage)

Benefits

Comp & perks

Negotiable / To be agreed